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Riccardo Pini

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#graph neural networks Open access Sep 2026

The Fractal Graph Rewriting Framework: A Scale-Dependent Approach to LLM Optimization

FGRF v3.0: Validated structural probe for LLM weight matrices, with spectral estimators and a reproducible trained-vs-untrained signature across Qwen2.5-0.5B, SmolLM2-360M, and GPT-2-medium. FGRF v2.0: Version 2 represents an evolution from the original proof-of-concept. It reframes FGRF from a direct optimizer into a structural integrity probe for neural networks. FGRF v1.0: Initial public release of the FGRF framework for optimizing LLMs without retraining.License: Code (.py files) is MIT licensed. Papers are CC BY-NC-ND licensed. See the LICENSE file in the repository for details.

Riccardo Pini · 0 citations
#graph neural networks Open access Sep 2026

The Fractal Graph Rewriting Framework: A Scale-Dependent Approach to LLM Optimization

FGRF v2.0: Version 2 represents an evolution from the original proof-of-concept. It reframes FGRF from a direct optimizer into a structural integrity probe for neural networks. FGRF v1.0: Initial public release of the FGRF framework for optimizing LLMs without retraining.License: Code (.py files) is MIT licensed. Papers are CC BY-NC-ND licensed. See the LICENSE file in the repository for details.

Riccardo Pini · 0 citations
#graph neural networks Open access Sep 2026

The Fractal Graph Rewriting Framework: A Scale-Dependent Approach to LLM Optimization

FGRF v2.0: Version 2 represents an evolution from the original proof-of-concept. It reframes FGRF from a direct optimizer into a structural integrity probe for neural networks. FGRF v1.0: Initial public release of the FGRF framework for optimizing LLMs without retraining.License: Code (.py files) is MIT licensed. Papers are CC BY-NC-ND licensed. See the LICENSE file in the repository for details.

Riccardo Pini · 0 citations

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